A portion of the disclosure of this patent document contains material which is subject to copyright protection. The copyright owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure, as it appears in the Patent and Trademark Office patent files or records, but otherwise reserves all copyright rights whatsoever.
An Appendix containing a computer program listing is submitted on a compact disc, which is incorporated by reference herein in its entirety. The total number of compact discs including duplicates is two. Each of the compact discs includes a file named xe2x80x9cRadiallmageCode.txtxe2x80x9d, which was created Jan. 26, 2001 and has a size of 44,826 bytes.
Logs are non-standard commodities that contain defects such as knots and cracks that significantly affect the value of boards cut from the log. Accordingly, when buying logs, a grader evaluates each log to determine the extent and locations of defects in the log. A sawyer, when cutting the log, attempts to select a sawing strategy that provides the highest value for the lumber cut from the log. These graders and sawyers typically depend on the external appearance of a log when grading or evaluating the log, but viewing the exterior of a log gives the grader or sawyer an imprecise indication of the quality of a log and often fails to indicate internal defects. This results in economic inefficiency because logs are inaccurately graded or cut.
Log scanning devices have been developed to improve the evaluation of logs and the optimization of sawing strategies. For example, U.S. Pat. No. 5,394,342 describes a scanning system that applies circumferentially spaced traverse scans along the length of a log to provide longitudinal density data. A paper by D. Schmoldt, entitled xe2x80x9cCT Imaging, Data Reduction, and Visualization of Hardwood Logs,xe2x80x9d Hardwood Symposium Proceedings, (May 1996) and a paper D. Schmoldt et al entitled xe2x80x9cNondestructive Evaluation of Hardwood Logs: CT Scanning, Machine Vision and Data Utilization,xe2x80x9d Nondestr. Test Eval., Vol. 15 (1999) describe CT (computer tomography) scanning of logs and evaluation of data resulting from CT scanning of a log.
The three-dimensional data structures and the large amount of data that scanners generate for a log are often difficult to use. For example, data indicating a three-dimensional density distribution for a log is difficult for a grader or sawyer to visualize, and computer manipulation of the large amount of data requires significant processing power or time. Efforts are continuing to improve the methods for quantifying the properties of logs, visualizing the data associated with the logs, and optimizing log grading and sawing strategies based on such data.
In accordance with an aspect of the invention, a three-dimensional density distribution for a log is processed to provide a convenient image or visualization of defects like knots or voids in a log and thereby facilitate grading and optimization of a sawing strategy for a log. The data representing such images has a two-dimensional structure and contains considerably less data than a three-dimensional density distribution. Accordingly, manipulation of data structures in accordance with the invention requires less processing power or time in automated processes for grading or optimization of a sawing strategy. Other aspects of the invention provide processes for grading and optimizing the sawing strategies based on the two-dimensional data structures.
In one embodiment, a visualization of a log provides a two-dimensional image where intensities (or colors) in the image correspond to a property evaluated along at least portions of cylindrical projections extending from the center of the log. Exemplary properties shown in the image include but are not limited to the average density along a projection, a minimum or maximum density along a projection, existence of a steep change in density along a projection, and flags indicating the presence or absence of defects along a projection. A central axis from which the projections extend can be straight or can follow the center of growth rings in the log, and the projections can be perpendicular to the axis or extend at an upward angle characteristic of the branches in a tree. A viewer of this image can quickly identify an orientation for the log that presents the fewest defects to a first cut of a saw blade.
One exemplary embodiment of the invention is a data structure for describing a log. The data structure includes a two-dimensional array of data values. Each data value corresponds to values of a coordinate Z and a second coordinate xcex8. The coordinate Z indicates distance along the log, and the coordinate xcex8 indicates an angle around the log. Each data value indicates a property of the log that is evaluated along a ray that originates at a center point corresponding to the value of the coordinate value Z and extends in a direction corresponding to the coordinate value xcex8. The center point at each value of the coordinate Z is typically the growth center of the log at that Z-coordinate value but alternatively can be the geometric center of the log or of core wood in the log. The ray evaluated to determine a data value can be perpendicular to the length of the log or directed at an upward angle along the log. The upward angle typically depends on a growth direction characteristic of tree limbs in the species of tree that produced the log or is determined independently for each log. Optionally, each data value indicates a property of the log that is evaluated in a range of distances along the ray that originates at the center point. The range can be limited to exclude core wood in the center of log and or bark on the outside of the log. In one specific embodiment, each data value indicates presence or absence of a defect corresponding to the coordinates of the data value and may further indicate the depth or location along the ray for any defect on the ray.
Another embodiment of the invention is a method for generating a description of a log. For a set of locations along the length of the log, the method finds a center point (e.g., a geometric or growth center) of the log. Each ray in a set of rays that extend from the center points is evaluated. In particular, the method evaluates a property of the log along each ray to generate a data value corresponding to Z and xcex8 coordinates identifying the direction of the ray. Typically, the evaluated property is density along the ray, and the evaluation determines whether there is a defect along the ray. A CT scan of the log can generate a three-dimensional data structure that provides the densities evaluated along the rays. A two-dimensional data structure that describes the log includes the data values, which are positioned in the two-dimensional data structure according to their respective coordinates.
Another embodiment of the invention is a system for evaluating logs. The system includes program code that is computer executable for manipulating a data structure such as described in the preceding paragraph. Generally, the system further includes a display device and a processor capable of executing the program code. In executing the program code, the processor controls display of an image on the display device. The image includes pixels that correspond to the data values of the data structure and have shades defined by the respective data values. The system can further superimpose marks on the image to indicate boundaries of one or more faces of the log that results from sawing the log. The marks can be shifted relative to the image identify an optimal orientation for sawing the log that minimizes the defects present between the boundary marks, i.e., in the cut faces of the log.
Another embodiment of the invention is method for grading a log. The grading method uses a two-dimensional defect structure or data array as described above that includes data values indexed by cylindrical or modified cylindrical coordinates. The grading method evaluates the two-dimensional array to determine sizes of blocks that are free of data values indicating defects. Each defect-free block contributes to a grade value of the log, according to the size of the block. Evaluation of the two-dimensional array can be performed manually, e.g., by a grader viewing an image having pixels shaded according to corresponding data values. The grader easily and quickly recognizes the sizes of the blocks through evaluating areas of the image having a shade indicating an absence of defects, and the grader can assign the grade to the log based on the viewing of the image. To aid the grader, superimposed marks in the image indicate boundaries of one or more board faces that results from a sawing strategy for the log, and the grader can shift the image relative to the marks to minimizes defects within the one or more board faces. The manual process can also select an orientation for sawing of the log according to positions of the marks that minimize defects in.the board faces.
The grading process can also be automated through a computer program that manipulates the two-dimensional array. One exemplary computer program includes: (a) determining a number N of data values that are consecutive in a direction of the coordinate xcex8 and correspond to a desired width of defect-free wood; (b) scanning the two-dimensional array in the direction of the coordinate xcex8 until identifying N consecutive data values that indicate absence of a defect; (c) scanning the two-dimensional array in a direction of the coordinate Z to determine a size of a block that is defect free; (d) increasing the grade value for the log by an amount corresponding to the size of the defect-free block; (e) repeating steps (b), (c), and (d) to account for all defect-free blocks in the two-dimensional data structure.
Another embodiment of the invention is an automated grading process that accounts for the sawing strategy and the optimal log orientation for the sawing strategy. An exemplary embodiment of this grading method includes: (a) creating a two-dimensional data or defect structure of a type described above; (b) selecting a sawing strategy for the log; (c) selecting an orientation of the log for the sawing strategy; (d) identifying a sub-array of the two-dimensional array, the sub-array corresponding to a face of the log resulting from the sawing strategy and the orientation; (e) evaluating the sub-array to determine sizes of blocks in the sub-array, that are free of data values indicating defects; (f) assigning a first grade value to the face according to the block sizes; (g) repeating steps (d), (e), and (f) for one or more faces of the log resulting from the sawing strategy and the orientation; (h) combining the grade values of the faces to generate a grade value for the orientation; and (i) repeating steps (c) to (h) for one or more additional orientations of the log; (j) assigning a grade value to the log based on a best of the grade values for the orientations.
Yet another embodiment of the invention is method for identifying a growth center of a log. The method determines an accumulated absolute value of a gradient of the density, or the number of zero crossings of the gradient, along lines through a cross-section of the log and identifies two crossing lines that have the largest accumulated values or the greatest numbers of zero crossings. The growth center is at the intersection of the crossing lines. Generally two sets of lines are considered, wherein the lines in the first set are perpendicular to the lines in the second set. To reduce the number of lines evaluated, the method can determine a geometric center of the log and select a small central area containing the geometric center of the log. The lines evaluated are limited to those passing through the central area. In accordance with a further aspect of the invention, considering only densities for points inside the central area when determining the accumulated absolute values of the gradient of the density reduces the complexity of the calculation.